{"id":"https://openalex.org/W2921317791","doi":"https://doi.org/10.23919/apsipa.2018.8659603","title":"Change Detection in High Resolution Satellite Images Using an Ensemble of Convolutional Neural Networks","display_name":"Change Detection in High Resolution Satellite Images Using an Ensemble of Convolutional Neural Networks","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2921317791","doi":"https://doi.org/10.23919/apsipa.2018.8659603","mag":"2921317791"},"language":"en","primary_location":{"id":"doi:10.23919/apsipa.2018.8659603","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012285390","display_name":"Kyungsun Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Kyungsun Lim","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014731019","display_name":"Dongkwon Jin","orcid":"https://orcid.org/0000-0002-6748-3284"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongkwon Jin","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063748248","display_name":"Chang\u2010Su Kim","orcid":"https://orcid.org/0000-0002-4276-1831"},"institutions":[{"id":"https://openalex.org/I197347611","display_name":"Korea University","ror":"https://ror.org/047dqcg40","country_code":"KR","type":"education","lineage":["https://openalex.org/I197347611"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chang-Su Kim","raw_affiliation_strings":["School of Electrical Engineering, Korea University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Korea University, Seoul, Korea","institution_ids":["https://openalex.org/I197347611"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012285390"],"corresponding_institution_ids":["https://openalex.org/I197347611"],"apc_list":null,"apc_paid":null,"fwci":3.7027,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.94028375,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"509","last_page":"515"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10111","display_name":"Remote Sensing in Agriculture","score":0.9804999828338623,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.782570481300354},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7389377355575562},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7199196815490723},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6804965734481812},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.632615327835083},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.5443869829177856},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5388625860214233},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.5212467312812805},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.45680421590805054},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4212425649166107},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4173874258995056},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32960474491119385}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.782570481300354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7389377355575562},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7199196815490723},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6804965734481812},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.632615327835083},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.5443869829177856},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5388625860214233},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5212467312812805},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.45680421590805054},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4212425649166107},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4173874258995056},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32960474491119385},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/apsipa.2018.8659603","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8500000238418579}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1836465849","https://openalex.org/W1857884451","https://openalex.org/W1901129140","https://openalex.org/W1972023946","https://openalex.org/W1979261208","https://openalex.org/W1998595580","https://openalex.org/W2036798369","https://openalex.org/W2068730661","https://openalex.org/W2108598243","https://openalex.org/W2111320133","https://openalex.org/W2117519593","https://openalex.org/W2139427956","https://openalex.org/W2144041313","https://openalex.org/W2144552105","https://openalex.org/W2153633422","https://openalex.org/W2155893237","https://openalex.org/W2157364932","https://openalex.org/W2161161768","https://openalex.org/W2194775991","https://openalex.org/W2216125271","https://openalex.org/W2300687442","https://openalex.org/W2317688867","https://openalex.org/W2325939864","https://openalex.org/W2415309533","https://openalex.org/W2417256080","https://openalex.org/W2461475918","https://openalex.org/W2519362791","https://openalex.org/W2615543373","https://openalex.org/W2737008123","https://openalex.org/W2750515003","https://openalex.org/W2766141718","https://openalex.org/W2777936741","https://openalex.org/W2778362064","https://openalex.org/W2962835968","https://openalex.org/W2964121744","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6699829263","https://openalex.org/W6700903540","https://openalex.org/W6726259354","https://openalex.org/W6745089958"],"related_works":["https://openalex.org/W2568858292","https://openalex.org/W1515964938","https://openalex.org/W2389381914","https://openalex.org/W4293226380","https://openalex.org/W2376528221","https://openalex.org/W2359428812","https://openalex.org/W3181296946","https://openalex.org/W196800607","https://openalex.org/W2258704520","https://openalex.org/W2969228573"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,108],"propose":[4],"a":[5,110],"novel":[6],"change":[7,65,91],"detection":[8,66],"algorithm":[9],"for":[10],"high":[11],"resolution":[12],"satellite":[13,34,99],"images":[14,117],"using":[15,77,114],"convolutional":[16],"neural":[17],"networks":[18],"(CNNs),":[19],"which":[20,89],"does":[21],"not":[22,72],"require":[23],"any":[24],"preprocessing,":[25],"such":[26],"as":[27],"ortho-rectification":[28],"and":[29,122],"classification.":[30],"When":[31],"analyzing":[32],"multi-temporal":[33],"images,":[35],"it":[36],"is":[37],"crucial":[38],"to":[39,60],"distinguish":[40],"viewpoint":[41],"or":[42,81],"color":[43],"variations":[44],"of":[45,97,105,148],"an":[46,94,146],"identical":[47],"object":[48],"from":[49,93],"actual":[50,132],"changes.":[51],"Especially":[52],"in":[53,119],"urban":[54],"areas,":[55],"the":[56,102,128,149],"registration":[57],"difficulty":[58],"due":[59],"high-rise":[61],"buildings":[62],"makes":[63],"conventional":[64],"techniques":[67],"unreliable,":[68],"if":[69],"they":[70],"are":[71,139],"combined":[73],"with":[74],"preprocessing":[75],"schemes":[76],"digital":[78],"surface":[79],"models":[80],"multi-spectral":[82],"information.":[83],"We":[84],"design":[85],"three":[86,150],"encoder-decoder-structured":[87],"CNNs,":[88,107],"yield":[90],"maps":[92],"input":[95],"pair":[96],"RGB":[98],"images.":[100],"For":[101],"supervised":[103],"learning":[104],"these":[106],"construct":[109],"large":[111],"fully-labeled":[112],"dataset":[113],"Google":[115],"Earth":[116],"taken":[118],"different":[120],"years":[121],"seasons.":[123],"Experimental":[124],"results":[125],"demonstrate":[126],"that":[127],"trained":[129],"CNNs":[130,151],"detect":[131],"changes":[133],"successfully,":[134],"even":[135],"though":[136],"image":[137],"pairs":[138],"neither":[140],"perfectly":[141],"registered":[142],"nor":[143],"color-corrected.":[144],"Furthermore,":[145],"ensemble":[147],"provides":[152],"excellent":[153],"performance,":[154],"outperforming":[155],"each":[156],"individual":[157],"CNN.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}